HYBRID RECOMMENDATION SYSTEM MEMANFAATKAN PENGGALIAN FREQUENT ITEMSET DAN PERBANDINGAN KEYWORD
Recommendation system was commonly built by manipulating item ranking data and user identity data. Item ranking data was a rare data on newly constructed system. Whereas, giving identity data to the recommendation system can cause concern about identity data misuse. Hybrid recommendation system used...
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| Format: | Thesis |
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[Yogyakarta] : Universitas Gadjah Mada
2015
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| _version_ | 1826049237579726848 |
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| author | PARWITA, WAYAN GEDE SUKA |
| author_facet | PARWITA, WAYAN GEDE SUKA |
| author_sort | PARWITA, WAYAN GEDE SUKA |
| collection | UGM |
| description | Recommendation system was commonly built by manipulating item ranking data and user identity data. Item ranking data was a rare data on newly constructed system. Whereas, giving identity data to the recommendation system can cause concern about identity data misuse. Hybrid recommendation system used frequent itemset mining algorithm and keyword comparison, it can provide recommendations without identity data and item ranking data. Frequent itemset mining was done using FP-Gwowth algorithm and keyword comparison with calculating document similarity value using cosine similarity approach. Hybrid recommendation system with a combination of frequent itemset mining and keywords comparison can give recommendations without using user identity and rating data. Hybrid recommendation system used 3 thresholds ie minimum similarity, minimum support, and number of recommendations. With the testing data used, precision, recall, F-measure, and MAP testing value are influenced by the threshold value. In addition, the usual problem in the best threshold can achieve a higher testing value than the coldstart problem both for the limited number of recommendations and the maximum recommendations. |
| first_indexed | 2024-03-13T23:42:45Z |
| format | Thesis |
| id | oai:generic.eprints.org:134519 |
| institution | Universiti Gadjah Mada |
| last_indexed | 2024-03-13T23:42:45Z |
| publishDate | 2015 |
| publisher | [Yogyakarta] : Universitas Gadjah Mada |
| record_format | dspace |
| spelling | oai:generic.eprints.org:1345192016-04-15T06:11:29Z https://repository.ugm.ac.id/134519/ HYBRID RECOMMENDATION SYSTEM MEMANFAATKAN PENGGALIAN FREQUENT ITEMSET DAN PERBANDINGAN KEYWORD PARWITA, WAYAN GEDE SUKA Information and Computing Sciences Information System Recommendation system was commonly built by manipulating item ranking data and user identity data. Item ranking data was a rare data on newly constructed system. Whereas, giving identity data to the recommendation system can cause concern about identity data misuse. Hybrid recommendation system used frequent itemset mining algorithm and keyword comparison, it can provide recommendations without identity data and item ranking data. Frequent itemset mining was done using FP-Gwowth algorithm and keyword comparison with calculating document similarity value using cosine similarity approach. Hybrid recommendation system with a combination of frequent itemset mining and keywords comparison can give recommendations without using user identity and rating data. Hybrid recommendation system used 3 thresholds ie minimum similarity, minimum support, and number of recommendations. With the testing data used, precision, recall, F-measure, and MAP testing value are influenced by the threshold value. In addition, the usual problem in the best threshold can achieve a higher testing value than the coldstart problem both for the limited number of recommendations and the maximum recommendations. [Yogyakarta] : Universitas Gadjah Mada 2015 Thesis NonPeerReviewed PARWITA, WAYAN GEDE SUKA (2015) HYBRID RECOMMENDATION SYSTEM MEMANFAATKAN PENGGALIAN FREQUENT ITEMSET DAN PERBANDINGAN KEYWORD. Masters thesis, UGM. http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=77200 |
| spellingShingle | Information and Computing Sciences Information System PARWITA, WAYAN GEDE SUKA HYBRID RECOMMENDATION SYSTEM MEMANFAATKAN PENGGALIAN FREQUENT ITEMSET DAN PERBANDINGAN KEYWORD |
| title | HYBRID RECOMMENDATION SYSTEM MEMANFAATKAN PENGGALIAN FREQUENT ITEMSET DAN PERBANDINGAN KEYWORD |
| title_full | HYBRID RECOMMENDATION SYSTEM MEMANFAATKAN PENGGALIAN FREQUENT ITEMSET DAN PERBANDINGAN KEYWORD |
| title_fullStr | HYBRID RECOMMENDATION SYSTEM MEMANFAATKAN PENGGALIAN FREQUENT ITEMSET DAN PERBANDINGAN KEYWORD |
| title_full_unstemmed | HYBRID RECOMMENDATION SYSTEM MEMANFAATKAN PENGGALIAN FREQUENT ITEMSET DAN PERBANDINGAN KEYWORD |
| title_short | HYBRID RECOMMENDATION SYSTEM MEMANFAATKAN PENGGALIAN FREQUENT ITEMSET DAN PERBANDINGAN KEYWORD |
| title_sort | hybrid recommendation system memanfaatkan penggalian frequent itemset dan perbandingan keyword |
| topic | Information and Computing Sciences Information System |
| work_keys_str_mv | AT parwitawayangedesuka hybridrecommendationsystemmemanfaatkanpenggalianfrequentitemsetdanperbandingankeyword |